Skip to main content
SpringerLink
Log in

Transport Accessibility and Spatial Connections of Cities in the Guangdong-Hong Kong-Macao Greater Bay Area

  • Published:
Chinese Geographical Science Aims and scope Submit manuscript

Abstract

Based on geographic information system (GIS) spatial analysis technology, the spatial pattern of raster grid transport accessibility for the Guangdong-Hong Kong-Macao Greater Bay area was studied and the states of spatial connectedness were simulated using highway passenger transport, railway passenger transport, port passenger transport and aviation passenger transport data. The result shows that transport accessibility within the Guangdong-Hong Kong-Macao Greater Bay area costs ‘one hour’ and the spatial distribution of accessibility in the area presents clear ‘core-periphery’ spatial characteristics, with Guangzhou, Foshan, Shenzhen constituting the core. The transport accessibility of Guangdong-Hong Kong-Macao is high. Average accessibility of urban nodes as measured by travel time is 0.99 h, and the areas accessible within 1.42 h occupy 79.14% of the total area. Most of the areas with the lowest accessibility are found in the peripheral area, with the worst accessibility being 4.73 h. Compared with the west-side cities, the economically developed east-side cities of the Guangdong-Hong Kong-Macao Greater Bay area have higher connectivity with roads, railways, ports, and aviation transport. Guangzhou, Foshan, Zhuhai, Shenzhen, Hong Kong and Macao are closely linked. The higher the accessibility, the closer the intercity connectedness.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Ahlström A, Pilesjö P, Lindberg J, 2011. Improved accessibility modeling and its relation to poverty–a case study in southern sri lanka. Habitat International, 35(2), 316–326. doi: 10.1016/ j.habitatint.2010.11.002

    Google Scholar 

  • Cao X S, Li L N, Wei H, 2017. Investigating intercity rail transit scope with social economy accessibility: case study of the Pearl River Delta region in China. Urban Rail Transit, 3(1): 61–71. doi: 10.1007/s40864-017-0058-0

    Google Scholar 

  • Cascetta E, 2009. Transportation Systems Analysis: Models and Applications (Vol. 29). Boston, MA: Springer Science & Business Media. doi: 10.1007/978-0-387-75857-2

    Google Scholar 

  • Chang J S, Lee J H, 2008. Accessibility analysis of Korean high-speed rail: a case study of the Seoul Metropolitan Area. Transport Reviews, 28(1): 87–103. doi: 10.1080/ 01441640701421495

    Google Scholar 

  • Cheng G, Zeng X K, Duan L et al., 2016. Spatial difference analysis for accessibility to high level hospitals based on travel time in Shenzhen, China. Habitat International, 53: 485–494. doi: 10.1016/j.habitatint.2015.12.023

    Google Scholar 

  • Cheng Y H, Chen S Y, 2015. Perceived accessibility, mobility, and connectivity of public transportation systems. Transportation Research Part A: Policy and Practice, 77: 386–403. doi: 10.1016/j.tra.2015.05.003

    Google Scholar 

  • Curtis C, Scheurer J., 2010. Planning for sustainable accessibility: developing tools to aid discussion and decision-making. Progress in Planning, 74(2): 53–106. doi: 10.1016/j.progress. 2010.05.001

    Google Scholar 

  • Deng Zhixin, 2017. Guangdong, Hong Kong and Macao Bay Area: the New Engine of the Pearl River delta. Guangdong Economy, (9): 32–35. (in Chinese)

    Google Scholar 

  • Duran-Fernandez R, Santos G A, 2014. A regional model of road accessibility in Mexico: accessibility surfaces and robustness analysis. Research in Transportation Economics, 46: 55–69. doi: 10.1016/j.retrec.2014.09.005

    Google Scholar 

  • El-Geneidy A, Levinson D, Diab E et al., 2016. The cost of equity: assessing transit accessibility and social disparity using total travel cost. Transportation Research Part A: Policy and Practice, 91: 302–316. doi: 10.1016/j.tra.2016.07.003

    Google Scholar 

  • Fischer M M, Wang J F, 2011. Spatial Data Analysis: Models, Methods and Techniques (SpringerBriefs in Regional Science). London: Springer Publishing Company, 47–59. doi: 10.1007/978-3-642-21720-3

    Google Scholar 

  • Ford A C, Barr S L, Dawson R J et al., 2015. Transport accessibility analysis using GIS: assessing sustainable transport in London. ISPRS International Journal of Geo-Information, 4(1): 124–149. doi: 10.3390/ijgi4010124

    Google Scholar 

  • GaWC, 2016. The world according to GaWC 2016. http://www.lboro.ac.uk/gawc/world2016t.html. Cited 19 March 2018.

    Google Scholar 

  • Geertman S C M, Ritsema Van Eck J R, 1995. GIS and models of accessibility potential: an application in planning. International Journal of Geographical Information Systems, 9(1): 67–80. doi: 10.1080/02693799508902025

    Google Scholar 

  • Getis A, Ord J K, 1996. Local spatial statistics: an overview. In: Longley P, Batty M (eds). Spatial Analysis Modelling in A Gis Environment. Cambridge: GeoInformation International, 14: 261–277.

    Google Scholar 

  • Geurs K T, Van Wee B, 2004. Accessibility evaluation of land-use and transport strategies: review and research directions. Journal of Transport Geography, 12(2): 127–140. doi: 10.1016/j. jtrangeo.2003.10.005

    Google Scholar 

  • Grengs J, Levine J, Shen Q et al., 2010. Intermetropolitan comparison of transportation accessibility: sorting out mobility and proximity in San Francisco and Washington, DC. Journal of Planning Education and Research, 29(4), 427–443. doi:10. 1177/0739456x10363278

    Google Scholar 

  • Gómez J N, Loures L, Castanho R et al., 2018. Assessing the feasibility of GIS multimethod approach to ascertain territorial accessibility to hemodynamics rooms in Spain mainland. Habitat International, 71: 22–28. doi: 10.1016/j.habitatint. 2017.11.001

    Google Scholar 

  • National Bureau of Statistics of China, 2017. China Statistics Abstract. Beijing: China Statistics Press.

    Google Scholar 

  • Gutiérrez J, González R, Gómez G, 1996. The European high-speed train network: predicted effects on accessibility patterns. Journal of Transport Geography, 4(4): 227–238. doi: 10.1016/S0966-6923(96)00033-6

    Google Scholar 

  • Gutiérrez J, Urbano P, 1996. Accessibility in the European Union: the impact of the trans-european road network. Journal of Transport Geography, 4(1): 15–25. doi: 10.1016/0966-6923(95)00042-9

    Google Scholar 

  • Guzman L A, Oviedo D, Rivera C, 2017. Assessing equity in transport accessibility to work and study: the Bogotá region. Journal of Transport Geography, 58: 236–246. doi: 10.1016/j. jtrangeo.2016.12.016

    Google Scholar 

  • Wixey S, Jones P, Lucas K et al., 2005. Measuring accessibility as experienced by different socially disadvantaged groups. London, Transit Studies Group, University of Westminster.

    Google Scholar 

  • Hansen W G, 1959. How accessibility shapes land use. Journal of the American Institute of Planners, 25(2): 73–76. doi: 10. 1080/01944365908978307

    Google Scholar 

  • Hawas Y E, Hassan M N, Abulibdeh A, 2016. A multi-criteria approach of assessing public transport accessibility at a strategic level. Journal of Transport Geography, 57: 19–34. doi: 10.1016/j.jtrangeo.2016.09.011

    Google Scholar 

  • Hou Q, Li S M, 2011. Transport infrastructure development and changing spatial accessibility in the Greater Pearl River Delta, China, 1990–2020. Journal of Transport Geography, 19(6): 1350–1360. doi: 10.1016/j.jtrangeo.2011.07.003

    Google Scholar 

  • Jiang H N, Xu W, Zhang W Z, 2018. Transportation accessibility and location choice of Japanese-Funded electronic information manufacturing firms in Shanghai. Sustainability, 10(2): 390. doi: 10.3390/su10020390

    Google Scholar 

  • Jiao Jingjuan, Wang Jiaoe, Jin Fengjun et al., 2016. Understanding relationship between accessibility and economic growth: a case study from China (1990–2010). Chinese Geographical Science, 26(6): 803–816. doi: 10.1007/s11769-016-0831-0

    Google Scholar 

  • Johnson D, Ercolani M, Mackie P, 2017. Econometric analysis of the link between public transport accessibility and employment. Transport Policy, 60: 1–9. doi: 10.1016/j.tranpol.2017. 08.001

    Google Scholar 

  • Kim H M, Kwan M P, 2003. Space-time accessibility measures: a geocomputational algorithm with a focus on the feasible opportunity set and possible activity duration. Journal of Geographical Systems, 5(1): 71–91. doi: 10.1007/s101090300104

    Google Scholar 

  • Kim K S, 2000. High-speed rail developments and spatial restructuring: a case study of the capital region in South Korea. Cities, 17(4): 251–262. doi: 10.1016/S0264-2751(00)00021-4

    Google Scholar 

  • Koenig J G, 1980. Indicators of urban accessibility: theory and application. Transportation, 9(2): 145–172. doi: 10.1007/ BF00167128

    Google Scholar 

  • Kwan M P, Janelle D G, Goodchild M F, 2003a. Accessibility in space and time: a theme in spatially integrated social science. Journal of Geographical System, 5(1): 1–3. doi: 10.1007/ s101090300100

    Google Scholar 

  • Kwan M P, Murray A T, O’Kelly M E et al., 2003b. Recent advances in accessibility research: representation, methodology and applications. Journal of Geographical Systems, 5(1): 129–138. doi: 10.1007/s101090300107

    Google Scholar 

  • Lau J C Y, Chiu C C H, 2004. Accessibility of workers in a compact city: the case of Hong Kong. Habitat International, 28(1): 89–102. doi: 10.1016/S0197-3975(03)00015-8

    Google Scholar 

  • Lau J C, 2006. Accessibility and the coping behaviour of the non-employed people in Hong Kong. Habitat International, 30: 1047–1055. doi: 10.1016/j.habitatint.2005.10.007

    Google Scholar 

  • Li H F, Calder C A, Cressie N, 2007. Beyond Moran’s I: testing for spatial dependence based on the spatial autoregressive model. Geographical Analysis, 39(4): 357–375. doi: 10.1111/ j.1538-4632.2007.00708.x

    Google Scholar 

  • Li L B, Ren H, Zhao S S et al., 2017. Two dimensional accessibility analysis of metro stations in Xi’an, China. Transportation Research Part A: Policy and Practice, 106: 414–426. doi: 10. 1016/j.tra.2017.10.014

    Google Scholar 

  • Li Lixun, 2017. Thinking on the Guangdong-Hong Kong-Macao greater bay area. Tropical Geography, 37(6): 757–761. (in Chinese)

    Google Scholar 

  • Mavoa S, Witten K, McCreanor T et al., 2012. GIS based destination accessibility via public transit and walking in Auckland, New Zealand. Journal of Transport Geography, 20(1): 15–22. doi: 10.1016/j.jtrangeo.2011.10.001

    Google Scholar 

  • Medda F, 2012. Land value capture finance for transport accessibility: a review. Journal of Transport Geography, 25: 154–161. doi: 10.1016/j.jtrangeo.2012.07.013

    Google Scholar 

  • Moran P A P, 1950. Notes on continuous stochastic phenomena. Biometrika, 37(1–2): 17–23. doi: 10.1093/biomet/37.1-2.17

    Google Scholar 

  • National Geomatics Center of China, 2017. 1:1 M-scale Topographic Database of the National Fundamental Geographic Information System of China, 2017. Beijing: Sinomap Press.

    Google Scholar 

  • Páez A, Scott D M, Morency C, 2012. Measuring accessibility: positive and normative implementations of various accessibility indicators. Journal of Transport Geography, 25: 141–153. doi: 10.1016/j.jtrangeo.2012.03.016

    Google Scholar 

  • Peng Fangmei, 2017. Economic spatial connection and spatial structure of Guangdong-Hong Kong-Macao Greater Bay and the surrounding area cities—An empirical analysis based on improved gravity model and social network analysis. Economic Geography, 37(12): 57–64. (in Chinese)

    Google Scholar 

  • Shen Q, 1998. Spatial technologies, accessibility, and the social construction of urban space. Computers, Environment and Urban Systems, 22(5): 447–464. doi: 10.1016/S0198-9715(98)00039-8

    Google Scholar 

  • Song H Y, Pan M M, Chen Y Y, 2016. Nightlife and public spaces in urban villages: a case study of the Pearl River Delta in China. Habitat International, 57: 187–204. doi: 10.1016/j. habitatint.2016.07.009

    Google Scholar 

  • Sun Dongqi, Lu Dadao, Wang Zhenbo, 2017. Predictive analysis of passenger and goods flow of Bohai Strait Cross-sea Channel. Acta Geographica Sinica, 72(8): 1486–1507. (in Chinese)

    Google Scholar 

  • Statistics Bureau of Guangdong Province and Guangdong Survey Office of National Bureau of Statistics, 2017. Guangdong Statistical Yearbook. Beijing: China Statistics Press.

    Google Scholar 

  • Tong L, Zhou X S, Miller H J, 2015. Transportation network design for maximizing space–time accessibility. Transportation Research Part B: Methodological, 81: 555–576. doi: 10.1016/ j.trb.2015.08.002

    Google Scholar 

  • Van Wee B, 2016. Accessible accessibility research challenges. Journal of Transport Geography, 51: 9–16. doi: 10.1016/j. jtrangeo.2015.10.018

    Google Scholar 

  • Vandenbulcke G, Steenberghen T, Thomas I, 2009. Mapping accessibility in Belgium: a tool for land-use and transport planning? Journal of Transport Geography, 17(1): 39–53. doi: 10. 1016/j.jtrangeo.2008.04.008

    Google Scholar 

  • Velaga N R, Beecroft M, Nelson J D et al., 2012. Transport poverty meets the digital divide: accessibility and connectivity in rural communities. Journal of Transport Geography, 21: 102–112. doi: 10.1016/j.jtrangeo.2011.12.005

    Google Scholar 

  • Vickerman R W, 1974. Accessibility, attraction, and potential: a review of some concepts and their use in determining mobility. Environment and Planning A, 6(6): 675–691. doi: 10.1068/ a060675

    Google Scholar 

  • Wang Haijiang, Miao Changhong, Niu Haipeng et al., 2016. Highway passenger transport contact and its spatial distribution in the central cities of China. Geographical Research, 35(4): 745–756. (in Chinese)

    Google Scholar 

  • Wang Z B, Xu G, Bao C et al., 2017. Spatial and economic effects of the Bohai Strait Cross-Sea Channel on the transportation accessibility in China. Applied Geography, 83: 86–99. doi: 10.1016/j.apgeog.2017.04.002

    Google Scholar 

  • Wang Zhengbo, Xu Jiangang, Fang Chuanglin et al., 2011. The study on county accessibility in China: characteristics and effects on population agglomeration. Journal of Geographical Sciences, 21(1): 18–34. doi: 10.1007/s11442-011-0826-9

    Google Scholar 

  • Weibull J W, 1976. An axiomatic approach to the measurement of accessibility. Regional Science and Urban Economics, 6(4): 357–379. doi: 10.1016/0166-0462(76)90031-4

    Google Scholar 

  • Wu C Y, Wei Y D, Huang X J et al., 2017a. Economic transition, spatial development and urban land use efficiency in the Yangtze River Delta, China. Habitat International, 63: 67–78. doi: 10.1016/j.habitatint.2017.03.012

    Google Scholar 

  • Wu Q T, Fan J, Zhang H O et al., 2017b. The spatial impacts model of trans-strait fixed links: a case study of the Pearl River Delta, China. Journal of Transport Geography, 63: 30–39. doi: 10.1016/j.jtrangeo.2017.07.003

    Google Scholar 

  • Yang Jun, Bao Yajun, Zhang Yuqing et al., 2018. Impact of accessibility on housing prices in Dalian City of China based on a geographically weighted regression model. Chinese Geographical Science, 28(3): 505–515. doi: 10.1007/s11769–018-0954-6.

    Google Scholar 

  • Yang W Y, Chen B Y, Cao X S et al., 2017. The spatial characteristics and influencing factors of modal accessibility gaps: a case study for Guangzhou, China. Journal of Transport Geography, 60: 21–32. doi: 10.1016/j.jtrangeo.2017.02.005

    Google Scholar 

  • Yang Yujun, Song Xiaodong, 2004. Comparing accessibility measures based on GIS. Journal of Chang’an University (Arch. & Envir. Science Edition), 21(4): 27–32. (in Chinese)

    Google Scholar 

  • Zhang Rui, 2017. Experience and enlightenment of world bay area economy development. China National Conditions and Strength, (5): 31–34. (in Chinese)

    Google Scholar 

  • Zhang W X, Nian P H, Lyu G W, 2016. A multimodal approach to assessing accessibility of a high-speed railway station. Journal of Transport Geography, 54: 91–101. doi: 10.1016/j.jtrangeo.2016.05.007

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Shool of Geography and Planning, Sun Yat-Sen University, Guangzhou, 510275, China

    Xiaoshu Cao, Shishu Ouyang, Yi Luo, Baochao Li & Dan Liu

  2. College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, 510642, China

    Wenyue Yang

Authors
  1. Xiaoshu Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shishu Ouyang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wenyue Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yi Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Baochao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Dan Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaoshu Cao.

Additional information

Foundation item: Under the auspices of National Natural Science Foundation of China (No. 41671160, 41701169)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cao, X., Ouyang, S., Yang, W. et al. Transport Accessibility and Spatial Connections of Cities in the Guangdong-Hong Kong-Macao Greater Bay Area. Chin. Geogr. Sci. 29, 820–833 (2019). https://doi.org/10.1007/s11769-019-1034-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11769-019-1034-2

Keywords

Search

Navigation